Whitepaper: Pooled Sample Testing: Optimal Strategy Determination using BRIDGEi2i Optimizer

Pooled Sample Testing: Optimal Strategy Determination using BRIDGEi2i Optimizer

The outbreak and spread of COVID-19 has altered the world and is likely to impact human civilization at multiple levels. While citizens are taking extreme caution with preventive measures, as of today, a sustainable solution, along the lines of a vaccine, is nowhere in sight. Instead, our energies are focused on arresting the spread of the pandemic by testing as many people as possible.

However, the scarcity of testing kits, given the density of people, is a major concern. In most countries, testing is only being carried out on patients who’re displaying symptoms of COVID-19, creating a gap that excludes asymptomatic people who may be carriers but remain mostly undetected.

A viable solution to bridge this gap is ‘Pooled Testing’, that involves gathering larger groups of subjects, split into sub-groups, and carrying out testing for said sub-groups, to identify the infection status of the entire group.

Curious about the details?

Take a look at how large-scale, sequential optimization can help assess the infection rates of larger groups, promoting faster calls-to-action to contain the pandemic spread!

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